{
  "id": 14903,
  "url": "https://arxiv.org/abs/2607.26055",
  "title": "πR^2: Reactive Real-time Flow Policies",
  "summary": "Generalist manipulation policies increasingly take the form of action-chunking flow policies built on large pretrained backbones. Such chunks run open-loop, so the policy cannot react to sensory input arriving mid-execution, sacrificing reactivity. Replanning more often would restore it, but the perception-to-action pipeline (a large backbone plus multiple denoising steps) is too slow: this latency forbids frequent replanning and leaves committed actions stale, making such policies ill-suited fo",
  "authors": "Sungjae Park, Shubham Tulsiani",
  "category": "research",
  "topics": "regulation",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-27T20:00:00.000Z",
  "fetched_at": "2026-07-31T05:10:57.675Z",
  "source_slug": "hf-daily",
  "source_name": "HuggingFace Daily Papers",
  "source_homepage": "https://huggingface.co/papers",
  "ethics_ai_record_url": "https://ethics.ai/record/14903",
  "original_url": "https://arxiv.org/abs/2607.26055",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}